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Contemporary Experimental Design, Multivariate Analysis and Data Mining = Festschrift in Honour of Professor Kai-Tai Fang /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Contemporary Experimental Design, Multivariate Analysis and Data Mining/ edited by Jianqing Fan, Jianxin Pan.
Reminder of title:	Festschrift in Honour of Professor Kai-Tai Fang /
other author:	Fan, Jianqing.
Description:	XVII, 386 p. 42 illus., 30 illus. in color.online resource. :
Contained By:	Springer Nature eBook
Subject:	Statistics . -
Online resource:	https://doi.org/10.1007/978-3-030-46161-4
ISBN:	9783030461614

Contemporary Experimental Design, Multivariate Analysis and Data Mining = Festschrift in Honour of Professor Kai-Tai Fang /
Contemporary Experimental Design, Multivariate Analysis and Data MiningFestschrift in Honour of Professor Kai-Tai Fang /[electronic resource] :edited by Jianqing Fan, Jianxin Pan. - 1st ed. 2020. - XVII, 386 p. 42 illus., 30 illus. in color.online resource.

Part I Review of Kai-Tai Fang’s Contribution -- 1 Walking on the Road to the Statistical Pyramid -- 2 The contribution to experimental designs by Kai-Tai Fang -- 3 From “Clothing Standard” to “Chemometrics” -- 4 A Review of Professor Kai-Tai Fang’s Contribution to the Education, Promotion, and Advancement of Statistics in China -- Part II Design of Experiments -- 5 Is a Transformed Low Discrepancy Design Also Low Discrepancy? -- 6 The construction of optimal design for order-of-addition experiment via threshold accepting -- 7 Construction of Uniform Designs on Arbitrary Domains by Inverse Rosenblatt Transformation -- 8 Drug Combination Studies, Uniform Experimental Design and Extensions -- 9 Modified robust design criteria for Poisson mixed models -- 10 Study of Central Composite Design and Orthogonal Array Composite Design -- 11 Uniform design on manifold -- Part III Multivariate Analysis -- 12 An Application of the Theory of Spherical Distributions in Multiple Mean Comparison -- 13 Estimating the Location Vector for Spherically Symmetric Distributions -- 14 On equidistant designs, symmetries and their violations in multivariate models -- 15 Estimation of covariance matrix with ARMA structure through quadratic loss function -- Part IV Data Mining -- 16 Depth Importance in Precision Medicine (DIPM): A Tree and Forest Based Method -- 17 Bayesian Mixture Models with Weight-Dependent Component Priors -- 18 Cosine Similarity-Based Classifiers for Functional Data -- Part V Hypothesis Test and Statistical Models -- 19 Projection Test with Sparse Optimal Direction for High-dimensional One Sample Mean Problem -- 20 Goodness-of-fit tests for correlated bilateral data from multiple groups -- 21 A Bilinear Reduced Rank Model -- 22 Simultaneous multiple change points estimation in generalized linear models -- 23 Data-Based Priors for Bayesian Model Averaging -- 24 Quantile regression with Gaussian kernels.

The collection and analysis of data play an important role in many ﬁelds of science and technology, such as computational biology, quantitative ﬁnance, information engineering, machine learning, neuroscience, medicine, and the social sciences. Especially in the era of big data, researchers can easily collect data characterised by massive dimensions and complexity. In celebration of Professor Kai-Tai Fang’s 80th birthday, we present this book, which furthers new and exciting developments in modern statistical theories, methods and applications. The book features four review papers on Professor Fang’s numerous contributions to the fields of experimental design, multivariate analysis, data mining and education. It also contains twenty research articles contributed by prominent and active figures in their fields. The articles cover a wide range of important topics such as experimental design, multivariate analysis, data mining, hypothesis testing and statistical models.

ISBN: 9783030461614

Standard No.: 10.1007/978-3-030-46161-4doiSubjects--Topical Terms:

1253516
Statistics .

LC Class. No.: QA276-280

Dewey Class. No.: 519.5

Contemporary Experimental Design, Multivariate Analysis and Data Mining = Festschrift in Honour of Professor Kai-Tai Fang /
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